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Record W2531321422 · doi:10.5539/jas.v8n11p179

Dust Reduction in Bauxite Waste: Role of Gypsum, Carbonation, and Microbial Decomposition

2016· article· en· W2531321422 on OpenAlex
Mark Anglin Harris

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2016
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsnot available
Fundersnot available
KeywordsCarbonationGypsumChemistryEnvironmental chemistryBauxiteSoil waterMineralogyAnimal scienceEnvironmental scienceMetallurgyMaterials scienceSoil science

Abstract

fetched live from OpenAlex

<p>Producing alumina by the Bayer Process creates fine air borne red dust which devalues property and causes irritation to the human respiratory system. Aggregation of such inorganic particles was proposed as a dust-inhibiting corrective. Resistance to breakdown under simulated rain suggests a lower number of dust-size particles after rain. Samples of red mud waste (1) treated 10 years before the study at the 0-15 cm depth zone with 40 t ha<sup>-1</sup> of gypsum (2) from the subjacent 15-30 cm zone, were collected, crushed and passed through a 0.5 mm diameter sieve. Leaves from <em>Acacia senensis</em> (a legume) were finely chopped to < 1 mm and thoroughly mixed with the sieved bauxite waste at 25- and 50%, and the samples incubated for 6 weeks at ambient room temperatures, at 60% soil water-holding capacity. To determine the fraction of potential dust, the treated samples were submerged in de-ionized water for several days until there was no change in discoloration (due to clay dislocation) of the water. The samples were removed from the water and the water evaporated and the residues dried and weighed. In total, the dust-reducing capabilities of the treatments in descending order of proficiency were: 50% phytogenic > 25% phytogenic > 0-15 cm soil depth non-phytogenic > 15-30 cm-depth non-phytogenic. The 50% phytogenic-treatment reduced potential particles of fugitive dust by 70% over the untreated controls and 95% over the crushed-only (subjacent red mud; no organics added) samples. All in all, phyto-organics increased average particle size to > 100 µm by flocculation, thereby creating stable agglomerates which resisted disintegration and breakdown under simulated rain. Reducing the concentration of < 75 μm particles in the air will decrease morbidity due to respiratory illnesses in surrounding populations, harmful effects on vegetation, and the defacement of buildings. This treatment promises the use of gypsum + phyto-organics for reducing the emanation of surface dust from red mud waste sites onto surrounding areas.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.103

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.197
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it